Knygos.lt klubas Knygos.lt nariams
83,57 €
-30%
Įprastai
119,39 €
Managing Intermittent Demand
Managing Intermittent Demand
Knygos.lt klubas Knygos.lt nariams
83,57 €
-30%
Įprastai
119,39 €
  • Išsiųsime per 12–18 d.d.
This work aims to increase the service level and to reduce the inventory costs by combining the forecast and inventory model into one consistent forecast-based inventory model. This new model is based on the prediction of the future probability distribution by assuming an integer-valued autoregressive process as demand process. The developed algorithms can be used to identify, estimate, and predict the demand as well as optimize the inventory decision of intermittent demand series. In an extens…

Managing Intermittent Demand (el. knyga) (skaityta knyga) | knygos.lt

Atsiliepimai

(4.00 Goodreads įvertinimas)

Aprašymas

This work aims to increase the service level and to reduce the inventory costs by combining the forecast and inventory model into one consistent forecast-based inventory model. This new model is based on the prediction of the future probability distribution by assuming an integer-valued autoregressive process as demand process. The developed algorithms can be used to identify, estimate, and predict the demand as well as optimize the inventory decision of intermittent demand series. In an extensive simulation study the new model is compared with a wide range of conventional forecast/inventory model combinations. By using the consistent approach, the mean inventory level is lowered whereas the service level is increased. Additionally, a modern multi-criteria inventory classification scheme is presented to distinguish different demand series clusters.

Knygos.lt klubas
Knygos.lt nariams
83,57 €
-30%
Įprastai
119,39 €
Kaina registruotiems pirkėjams
Prisijunkite ir už šią prekę
gausite 1,19 Knygų Eurų!?
Išsiųsime per 12–18 d.d.
Įsigykite dovanų kuponą
Daugiau

This work aims to increase the service level and to reduce the inventory costs by combining the forecast and inventory model into one consistent forecast-based inventory model. This new model is based on the prediction of the future probability distribution by assuming an integer-valued autoregressive process as demand process. The developed algorithms can be used to identify, estimate, and predict the demand as well as optimize the inventory decision of intermittent demand series. In an extensive simulation study the new model is compared with a wide range of conventional forecast/inventory model combinations. By using the consistent approach, the mean inventory level is lowered whereas the service level is increased. Additionally, a modern multi-criteria inventory classification scheme is presented to distinguish different demand series clusters.

Atsiliepimai

  • Atsiliepimų nėra
0 pirkėjai įvertino šią prekę.
5
0%
4
0%
3
0%
2
0%
1
0%
(rodomas nebus)